I am writing a simple python code to fit two Lorentzians to my data.
I am facing an error in the Fit function where I have set
OutputCompositeMembers=True
and
EvaluationType=“Histogram”
but this returns the following error:
RuntimeError Traceback (most recent call last)
in ()
33 #using the fit function for each workspace i
34 fit_out = Fit(Function=function,InputWorkspace=“sample”,WorkspaceIndex=i,StartX=-0.29, EndX=1.1,
—> 35 CreateOutput=True,Output=“fit_results”,MaxIterations=500,EvaluationType=‘Histogram’,OutputCompositeMembers=True)
36 #setting the parameters to the values
37 chi_sq = fit_out[1]/opt/Mantid/bin/mantid/simpleapi.pyc in wrapper(*Function, InputWorkspace, ****kwargs)
365 del kwargs[key]
366 set_properties(algm, **kwargs)
→ 367 algm.execute()
368 return _gather_returns(function_name, lhs, algm, inout=inout)
369 # endRuntimeError: Integration is not implemented for this function.
But if I use CentrePoint evaluation type, this error is not encountered, but the fitting is quite poor.
PS : This is the whole script, highlighted the relevant values in bold
test = True
counter = 100
#starting values for all four parameters
g1[0] = 0.01 #initial value for g1
g2[0] = 0.1 #initial value for g2
a0[0] = 1e-2
a1[0] = 1e-2
for i in range(0,Qvalues):
test = True
while( test ):
function_composition = “(composite=Convolution,FixResolution=true,NumDeriv=true;”#composite function of convolution type
function_composition += “name=TabulatedFunction,Workspace=res,”#resolution workspace
function_composition += “WorkspaceIndex=”+str(i) #using the appropriate Q-valued resolution function.
function_composition += “,Scaling=1,Shift=0,XScaling=1,ties=(Scaling=1,Shift=0,XScaling=1);”
lorentzian_0 = “(name=Lorentzian”
lorentzian_0 += “,Amplitude=”+str(a0[i])
lorentzian_0 += “,PeakCentre=”+str(0.0)
lorentzian_0 += “,FWHM=”+str(g1[i])
ties_l0 = “” #leaving this open to add any constraints to lorentzian 1
constraints_l0 = “”
lorentzian_1 = “;name=Lorentzian”
lorentzian_1 += “,Amplitude=”+str(a1[i])
lorentzian_1 += “,PeakCentre=”+str(0.0)
lorentzian_1 += “,FWHM=”+str(g2[i])
constraints_l1 = “”
ties_l1 = “)” #leaving this open to add any constraints to lorentzian 1
bg_function_string = “);name=LinearBackground,A0=0,A1=0” #background is chosen linear
function = function_composition+lorentzian_0+ties_l0+lorentzian_1+ties_l1+bg_function_string
#print function
#using the fit function for each workspace i
fit_out = Fit(Function=function,InputWorkspace=“sample”,WorkspaceIndex=i,StartX=-0.29, EndX=1.1,
CreateOutput=True,Output=“fit_results”,MaxIterations=500,EvaluationType=‘Histogram’,OutputCompositeMembers=True)
#setting the parameters to the values
chi_sq = fit_out[1]
a0[i] = fit_out[3].row(3)[“Value”]
g1[i] = fit_out[3].row(5)[“Value”]
a1[i] = fit_out[3].row(6)[“Value”]
g2[i] = fit_out[3].row(8)[“Value”]
if (i <7):
a0[i+1], a1[i+1], g1[i+1], g2[i+1] = a0[i],a1[i],g1[i],g2[i]
if ( chi_sq < 3.0):
test = False
#just printing params after successful fitting
print (“Parameters obtained after “+str(i)+“th Q-value fitting”)
print qs[i],a0[i],a1[i],g1[i],g2[i],” Chi-qs: “,chi_sq
#store the fit of functions in sqw_fit for each Q-value
fit_Evalues = fit_out[4].blocksize()
#print fit_Evalues+1,fit_out[4].readX(1).size
energy_fit[:fit_Evalues+1] = fit_out[4].readX(1)
sqw_fit[i,:fit_Evalues] = fit_out[4].readY(1)
print(”\n”)
print(“Fitting done for all Q-values”)
, am trying to carry out everything from reduction to analysis with Mantid, the reason why I am trying the best I can.